This purely theoretical work investigates the problem
of artificial singularities in camera self-calibration. Selfcalibration
allows one to upgrade a projective reconstruction
t...
We show how carefully crafted random matrices can achieve distance-preserving dimensionality reduction, accelerate spectral computations, and reduce the sample complexity of certai...
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
Spectral clustering has attracted much research interest in recent years since it can yield impressively good clustering results. Traditional spectral clustering algorithms first s...
Bo Chen, Bin Gao, Tie-Yan Liu, Yu-Fu Chen, Wei-Yin...
The issue of multiuser cooperation in a complexity constrained noise-free CDMA channel is addressed. Multiuser cooperation is imperative if conventional demodulation is expected to...